Optimal Personalized Treatment Selection with Multivariate Outcome Measures in a Multiple Treatment Case.

ABSTRACT: In this work we propose a novel method for individualized treatment selection when there are correlated multiple treatment responses. For the K treatment (K ≥ 2) scenario, we compare quantities that are suitable indexes based on outcome variables for each treatment conditional on patient-specific scores constructed from collected covariate measurements. Our method covers any number of treatments and outcome variables, and it can be applied for a broad set of models. The proposed method uses a rank aggregation technique that takes into account possible correlations among ranked lists to estimate an ordering of treatments based on treatment performance measures such as the smooth conditional mean. The method has the flexibility to incorporate patient and clinician preferences i

SUBMITTER: Siriwardhana C 

PROVIDER: S-EPMC10871612 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature